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Relationship: 376

Title

A descriptive phrase which clearly defines the two KEs being considered and the sequential relationship between them (i.e., which is upstream, and which is downstream). More help

Covalent Binding, Protein leads to Response, Keratinocytes

Upstream event

The causing Key Event (KE) in a Key Event Relationship (KER). More help

Covalent Binding, Protein

Downstream event

The responding Key Event (KE) in a Key Event Relationship (KER). More help

Response, Keratinocytes

Key Event Relationship Overview

The utility of AOPs for regulatory application is defined, to a large extent, by the confidence and precision with which they facilitate extrapolation of data measured at low levels of biological organisation to predicted outcomes at higher levels of organisation and the extent to which they can link biological effect measurements to their specific causes.Within the AOP framework, the predictive relationships that facilitate extrapolation are represented by the KERs. Consequently, the overall WoE for an AOP is a reflection in part, of the level of confidence in the underlying series of KERs it encompasses. Therefore, describing the KERs in an AOP involves assembling and organising the types of information and evidence that defines the scientific basis for inferring the probable change in, or state of, a downstream KE from the known or measured state of an upstream KE. More help

AOPs Referencing Relationship

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) that help to define the biological applicability domain of the KER.In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER. More help

Sex Applicability

An indication of the the relevant sex for this KER. More help

Life Stage Applicability

An indication of the the relevant life stage(s) for this KER. More help

Key Event Relationship Description

Provides a concise overview of the information given below as well as addressing details that aren’t inherent in the description of the KEs themselves. More help

Haptens can also react with cell surface proteins and activate response pathways in keratinocytes (see ^[1]). Uptake of the hapten by keratinocytes activates multiple events, including the release of pro-inflammatory cytokines and the induction of cyto-protective cellular pathways. Activation of the pro-inflammatory cytokine IL-18 results from cleavage of inactive IL-18 precursor protein by inflammasome-associated caspase-1^[2]. Sensitizers can activate the inflammasome (^[3];^[4]) and in so doing induce IL-18 production. Intracellular Nodlike receptors (NLR) contain sensors for a number of cellular insults. Upon activation (by a currently unknown mechanism), NLRs oligomerise form molecular complexes (i.e. inflammasomes) that are involved in the activation of inflammatory-associated caspases, including caspase-1. Inductions of intracellular levels of IL-18 exhibit responses upon exposure to sensitizers which can be used to establish potency^[5].

Keratinocyte exposure to sensitizers also results in induction of antioxidant/electrophile response element ARE/EpRE-dependent pathways^[6]. Briefly, reactive chemicals bind to Keap1 (Kelch-like ECH-associates protein 1) that normally inhibit the nuclear erythroid 2-related factor 2 (Nrf2). Released Nrf2 interacts with other nuclear proteins and binds to and activates ARE/EpREdependent pathways, including the cytoprotective genes NADPH-quinone oxidoreductase 1 (NQ01) and glutathione S-transferase (GSHST), among others (^[6];^[7]).

Evidence Collection Strategy

Include a description of the approach for identification and assembly of the evidence base for the KER. For evidence identification, include, for example, a description of the sources and dates of information consulted including expert knowledge, databases searched and associated search terms/strings. Include also a description of study screening criteria and methodology, study quality assessment considerations, the data extraction strategy and links to any repositories/databases of relevant references.Tabular summaries and links to relevant supporting documentation are encouraged, wherever possible. More help

Evidence Map 2.0

ID	Experimental Design	Species	Upstream Observation	Downstream Observation	Citation (first author, year)	Notes

Evidence Map

Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP. More help

Title	First Author	Biological Plausibility	Dose Concordance	Temporal Concordance	Incidence Concordance

Biological Plausibility

Dose Concordance Evidence

Temporal Concordance Evidence

Incidence Concordance Evidence

Uncertainties and Inconsistencies

Addresses inconsistencies or uncertainties in the relationship including the identification of experimental details that may explain apparent deviations from the expected patterns of concordance. More help

Uncertainties include the structural and physicochemical cut-offs between theoretical and measured reactivity (^[12]), the significance of the preferred amino acid target (e.g., cysteine versus lysine) (OECD, 2011b), the significance of Th1 or type 1 (IFN-γ) versus Th2 or type 2 (IL-2, IL-4, IL-13) cytokine secretion profiles (^[13]), and sensitisation measurements in different in vivo models.

Inconsistencies within the reported data are seen. There are differences between in vitro responses for highly similar chemicals (see^[6];^[14]). There are differences within and between in vivo test results for highly similar chemicals (see Annex C of the European Centre for Ecotoxicological and Toxicological Chemicals, 2010). Highly hydrophobic chemicals, which are in vivo sensitizers, are not active in aquatic-based in chemico or in vitro assays. The specific nature of the relationship between irritation and sensitisation has yet to be elucidated.

Data gaps: Based on the more than 50 chemical reactions associated with covalent binding to thiol or primary amine moieties^[15] in vitro data for keratinocyte, dendritic cell, and T-cell assays, as well as in vivo sensitisation data, is incomplete in that it does not cover the chemical spaces associated with many of these chemical reactions; in chemico data is also incomplete, especially for reactions that favour amino acid targets other than cysteine.

Known modulating factors

This table captures specific information on the MF, its properties, how it affects the KER and respective references.1.) What is the modulating factor? Name the factor for which solid evidence exists that it influences this KER. Examples: age, sex, genotype, diet 2.) Details of this modulating factor. Specify which features of this MF are relevant for this KER. Examples: a specific age range or a specific biological age (defined by...); a specific gene mutation or variant, a specific nutrient (deficit or surplus); a sex-specific homone; a certain threshold value (e.g. serum levels of a chemical above...) 3.) Description of how this modulating factor affects this KER. Describe the provable modification of the KER (also quantitatively, if known). Examples: increase or decrease of the magnitude of effect (by a factor of...); change of the time-course of the effect (onset delay by...); alteration of the probability of the effect; increase or decrease of the sensitivity of the downstream effect (by a factor of...) 4.) Provision of supporting scientific evidence for an effect of this MF on this KER. Give a list of references. More help

Quantitative Understanding of the Linkage

Captures information that helps to define how much change in the upstream KE, and/or for how long, is needed to elicit a detectable and defined change in the downstream KE. More help

Is it known how much change in the first event is needed to impact the second? Are there known modulators of the response-response relationships? Are there models or extrapolation approaches that help describe those relationships?

An in vitro reporter assay based on activation via the ARE/EpRE response element has been shown to be responsive to known sensitizers in HaCaT keratinocytes^[16]. Expression of ARE/EpRE-dependent genes and other cytoprotective genes (including CYP1A1, MT1 and MT2) in HaCaT cells are part of a proprietary in vitro battery approach to determining sensitisation potency (^[14]). Both the Natsch and McKim groups have shown that this signalling pathway responds in a quantitative fashion, which is related to LLNA potency (e.g. strong, moderate, and weak).

Response-response Relationship

Provides sources of data that define the response-response relationships between the KEs. More help

Time-scale

Information regarding the approximate time-scale of the changes in KEdownstream relative to changes in KEupstream (i.e., do effects on KEdownstream lag those on KEupstream by seconds, minutes, hours, or days?). More help

Known Feedforward/Feedback loops influencing this KER

Define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits. More help

Domain of Applicability

A free-text section of the KER description that the developers can use to explain their rationale for the taxonomic, life stage, or sex applicability structured terms. More help

While in vivo testing focuses on selected mammals including man, the key events for this AOP appear to be conserved across mammals. With exceptions, there is agreement between sensitizers initiated by covalent binding to proteins and non-sensitizers tested in mice, guinea-pigs, and humans; this is especially the case for extreme and strong sensitizers but lesser so for weak and non-sensitizers. One problem is that earlier results, especially with the guinea-pig, were not dose-response experiments. Chemical reactivity data show very good concordance of dose-response relationships regardless of the method. In general, available data from in vitro assays are fragmentary and often qualitative (i.e., yes/no).